有没有一个用于CPU输入的torch._C._nn.nll_loss函数？我没有足够的GPU内存来运行我的函数，所以我想尝试在CPU上运行所有内容。这是我的具体错误（请查看anaconda文件）

Traceback (most recent call last):  File "plot_parametric_pytorch.py", line 395, in <module>    val_result = validate(val_loader, model, criterion, 0)  File "plot_parametric_pytorch.py", line 228, in validate    training=False, optimizer=None)  File "plot_parametric_pytorch.py", line 169, in forward    loss = criterion(output, target_var)  File "/home/klee/anaconda3/envs/sharpenv/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__    result = self.forward(*input, **kwargs)  File "/home/klee/anaconda3/envs/sharpenv/lib/python3.7/site-packages/torch/nn/modules/loss.py", line 932, in forward    ignore_index=self.ignore_index, reduction=self.reduction)  File "/home/klee/anaconda3/envs/sharpenv/lib/python3.7/site-packages/torch/nn/functional.py", line 2317, in cross_entropy    return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction)  File "/home/klee/anaconda3/envs/sharpenv/lib/python3.7/site-packages/torch/nn/functional.py", line 2115, in nll_loss    ret = torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)RuntimeError: Expected object of device type cuda but got device type cpu for argument #1 'self' in call to _thnn_nll_loss_forward

回答：

nll_loss 可以同时在CPU和GPU上运行，但输入和目标需要在同一设备上。您的输入和目标位于不同设备上，第一个（output）在CPU上，第二个（target_var）在GPU上。

您需要将target_var放到CPU上。

loss = criterion(output, target_var.cpu())